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Hybrid algorithm for damping controller design in electric power systems via genetic algorithms and gradient descent

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Author(s):
Marcelo Favoretto Castoldi
Total Authors: 1
Document type: Doctoral Thesis
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD)
Defense date:
Examining board members:
Rodrigo Andrade Ramos; Newton Geraldo Bretas; Romeu Reginatto; Luiz Carlos Pereira da Silva; Eduardo do Valle Simões
Advisor: Rodrigo Andrade Ramos; Newton Geraldo Bretas
Abstract

Electric Power Systems are constantly subjected to perturbations, which can be caused for several different reasons, e.g., due to a sudden load increase or a short circuit in a transmission line. These perturbations can induce electromechanical oscillations in the power system, since the angular speed of the generators oscillates. To reduce such oscillations, power system controllers are used, and the most common ones are the PSSs (Power System Stabilizers). In some systems, however, the usage of PSSs is not sufficient to guarantee a satisfactory level for the minimum damping, being necessary the usage of other types of controllers. Hence, FACTS (Flexible Alternating Current Transmission System) controllers, specially the TCSC (Thyristor Controlled Series Capacitor), became an attractive alternative to enhance the damping of electric power systems. The TCSC control action is performed by a POD (Power Oscillation Damper) controller, which is a supplementary control function of the device. However, it is not only the usage of such controllers that guarantees a sufficient damping, but also a good tuning of their parameters. The tuning of such controllers is ordinarily performed manually, using a trial-and-error method, which can last for a long time, even for experienced engineers. To facilitate the designers work in the tuning of the controllers parameters, automatic tuning methods are being studied. Such methods have the main advantage of considering several operating points of the system simultaneously, yielding a robust controller regarding variations in its nominal operating point. The aforementioned automatic tuning methods use local optimization methods or global optimization methods. The local optimization methods have the speed as the main advantage, but they can have convergence issues in the search for the minimum satisfactory damping threshold desired by the designer. The global optimization methods, on the other hand, ordinarily converge for the desired minimum damping threshold, but with large convergence times. This work proposes a controller tuning method using a hybrid structure, i.e., global search methods with local search methods. Initially, a global search is performed by the algorithm until a stop criteria is met, as defined by the designer (usually a minimum damping for the system). Thus, the controller parameters tuned by the global search method are the input values of a local search method. The local search algorithm actually refines the controllers tuning, increasing the system damping to the value defined by the designer. In this work the global search is performed by a genectic algorithm while the local search is performed by an algorithm based in the gradient descent of objective function (damping in this case). The greatest advantages of the proposed algorithm are the possible decrease in computational time and effort, when compared to global search methods, verified in the work results. (AU)

FAPESP's process: 07/00062-5 - Damping controls in electrical power systems: a LMI-based approach design
Grantee:Marcelo Favoretto Castoldi
Support Opportunities: Scholarships in Brazil - Doctorate